The overarching goal of this application is to develop the Dartmouth Cystic Fibrosis Research Center (DartCF), building on our strong history of CF-related research in lung infection, inflammation/immunity and translational science, by expanding our capability to investigate host-microbe interactions in the gut, and their impact on gut dysbiosis and overall systemic health of CF-related diabetes patients. The primary objective of the Applied Bioinformatics and Biostatistics Core (ABBC) is to provide expert-level bioinformatics and biostatistical support and training to DartCF faculty and trainees, our partnering institutions, and to peer P30 CF Centers. State-of-the-art bioinformatics and biostatistics support is critical for the successful generation and analysis of large CF date sets. In fact, the lack of expert-level informatics and statistical support for big data studies is one of the most significant limitations to CF research. To start addressing this challenge, five years ago our Lung Biology Center developed a program to recruit and train CF scientists from diverse scientific disciplines to utilize bioinformatics and biostatistical tools for analyzing large data sets. Our program now has two CF scientists who provide expert bioinformatics/biostatistics support to advance the research of DartCF faculty and trainees, and our collaborators. Importantly, our lead data analysts have trained dozens of CF scientists to the level of mastery in bioinformatics skills relevant to their research. These scientists actively promote and use bioinformatics in their home laboratories, and two are participating as instructors in our educational programs. We have built a system capable of sustainable, efficient growth to meet ever-increasing demands. Our instructional system includes weekly meetings (R Club) and seminars at which students and faculty present their research using statistical, graphical, and informatics tools. In addition, we host two short, but intensive, courses to provide training in the technical and statistical foundations of applied bioinformatics, and a yearly course on the Biology of CF for trainees and biomedical data scientists. Bioinformatics course content ranges from basic topics like programming in R and how to use high performance computing systems, to more advanced topics such as systems biology, integrative biology, and machine learning. Both instructional components are constantly evolving in response to changing technology and feedback from students, just as our hardware and software development agenda is driven by the needs of our scientific partners. To remain focused on DartCF research goals and education, we will take full advantage of best-of-breed purchased solutions as well as support from Dartmouth?s Research Computing and the Department of Biomedical Data Science. To leverage the large amount of CF metagenomic data currently stored in disparate information systems throughout the CF research community, and promote bioinformatics collaboration, we will work with peer CF research institutions to establish data standards and prototype a cystic fibrosis metagenomic data repository (CFMDR).